class_docstr: Constructs a Speech2Text processor which wraps a Speech2Text feature extractor and a Speech2Text tokenizer into a
  single processor.
  
  [`Speech2TextProcessor`] offers all the functionalities of [`Speech2TextFeatureExtractor`] and
  [`Speech2TextTokenizer`]. See the [`~Speech2TextProcessor.__call__`] and [`~Speech2TextProcessor.decode`] for more
  information.
  
  Args:
      feature_extractor (`Speech2TextFeatureExtractor`):
          An instance of [`Speech2TextFeatureExtractor`]. The feature extractor is a required input.
      tokenizer (`Speech2TextTokenizer`):
          An instance of [`Speech2TextTokenizer`]. The tokenizer is a required input.
docstr: When used in normal mode, this method forwards all its arguments to Speech2TextFeatureExtractor's
  [`~Speech2TextFeatureExtractor.__call__`] and returns its output. If used in the context
  [`~Speech2TextProcessor.as_target_processor`] this method forwards all its arguments to Speech2TextTokenizer's
  [`~Speech2TextTokenizer.__call__`]. Please refer to the doctsring of the above two methods for more
  information.
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code: def __call__(self, *args, **kwargs):
      """
      When used in normal mode, this method forwards all its arguments to Speech2TextFeatureExtractor's
      [`~Speech2TextFeatureExtractor.__call__`] and returns its output. If used in the context
      [`~Speech2TextProcessor.as_target_processor`] this method forwards all its arguments to Speech2TextTokenizer's
      [`~Speech2TextTokenizer.__call__`]. Please refer to the doctsring of the above two methods for more
      information.
      """
      # For backward compatibility
      if self._in_target_context_manager:
          return self.current_processor(*args, **kwargs)
  
      if "raw_speech" in kwargs:
          warnings.warn(
              "Using `raw_speech` as a keyword argument is deprecated. Use `audio` instead."
          )
          audio = kwargs.pop("raw_speech")
      else:
          audio = kwargs.pop("audio", None)
      text = kwargs.pop("text", None)
      if len(args) > 0:
          audio = args[0]
          args = args[1:]
  
      if audio is None and text is None:
          raise ValueError(
              "You need to specify either an `audio` or `text` input to process."
          )
  
      if audio is not None:
          inputs = self.feature_extractor(audio, *args, **kwargs)
      if text is not None:
          encodings = self.tokenizer(text, **kwargs)
  
      if text is None:
          return inputs
      elif audio is None:
          return encodings
      else:
          inputs["labels"] = encodings["input_ids"]
          return inputs
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/src/transformers/models/speech_to_text/processing_speech_to_text.py
imports: import warnings
  from contextlib import contextmanager
  from ...processing_utils import ProcessorMixin
label_desc: Use image node_id 2 for calling the Speech2TextProcessor obj's underlying member method code with example usage: obj.__call__() and returns: self, inputs, encodings, inputs